Andrew G. Haldane, Chief Economist at the Bank of England gave a speech titled “Labor’s Share” at the Trades Union Congress in London, England on Nov. 12, 2015.

In it he warned that robots may destroy some 15 million jobs in England over the coming decades, nearly half of all employment.

Here is a brief excerpt (the full speech can be found here):

In sum, the third industrial evolution appears to have resulted in an intensification of trends already fledgling in the first two:  a hollowing-out of employment, a widening distribution of wages and a fall in labour’s income share.  The key question is what happens next?  A re-run of the 19th century, with productivity gains eventually boosting wages and the labour share?  Or, different than in the past, a permanent re-shaping of the labour landscape?

A number of authors have recently argued, persuasively, that it is the latter.  Based on past patterns, it is argued that information technology may be poised for exponential growth, as its full fruits are harvested.  Indeed, we may be on the cusp of a fourth Industrial Revolution or Second Machine Age (Brynjolfsson and McAfee (2014), Ford (2015)).

Its defining feature would be that new-age machines will be thinking as well as doing, sensing as well as sifting, adapting as well as enacting.  They will thus span a much wider part of the skill distribution than ever previously.  As robots extend their skill-reach, “hollowing-out” may thus be set to become ever-faster, ever-wider and ever-deeper.  Or that, at least, is the picture some have painted paint.

How much wider and deeper?   Research by Carl Benedikt Frey and Michael Osborne has tried to quantify this hollowing-out, by assigning probabilities to certain classes of job being automated over the course of the next few decades.  Their work was initially done for the US, but has recently been extended to the UK (Frey and Osbourne (2013), Deloitte (2015b))..

Using this methodology, the Bank has recently done its own exercise for the UK.  Table 3 classifies jobs three ways in the US and UK – high (greater than 66%), medium (33-66%) and low (less than 33%) probability of automation.  It also shows the fraction of employment these jobs represent.  Chart 27 provides a more granular breakdown of these jobs.

For the UK, roughly a third of jobs by employment fall into each category, with those occupations most at risk including administrative, clerical and production tasks.  Taking the probabilities of automation, and multiplying them by the numbers employed, gives a broad brush estimate of the number of jobs potentially automatable.  For the UK, that would suggest up to 15 million jobs could be at risk of automation.  In the US, the corresponding figure would be 80 million jobs.